As the United States approaches the November 3 midterm elections, the growing prominence of prediction markets has sparked debate over their influence and potential risks. Platforms such as Polymarket and Kalshi facilitate trading on election outcomes and other political events, with combined monthly trading volumes reaching $53 billion by July 2026, more than double that of just two months earlier. These markets allow users to buy and sell contracts linked to various scenarios, ranging from candidates winning races to specific political behaviors.
The increasing visibility of these markets has been amplified by partnerships with major news organizations. Networks including CNN, CNBC, and Fox News incorporate prediction market odds into election coverage, with live tickers and social media projections influencing public perceptions. Experts express concern that this prominence may blur the distinction between market-based probabilities and actual vote counts, potentially misleading voters or fueling unfounded claims of election fraud. President Donald Trump, for instance, has made unsubstantiated fraud allegations a core aspect of his campaign rhetoric ahead of the elections.
Advocates argue that prediction markets offer valuable insight distinct from traditional polling by reflecting the real-money bets of participants, which may aggregate diverse information and sentiment. Kalshi’s communications director, Elisabeth Diana, describes these platforms as complements to polling, emphasizing that trading represents what users think will happen rather than what they hope for. Economist Robin Hanson, who contributed to the development of prediction market theory, contends that allowing insiders to participate can enhance market accuracy.
However, concerns about the susceptibility of prediction markets to manipulation and misuse persist. Campaign candidates and staffers have at times placed bets on races they are involved in, prompting fines and suspensions. In 2026, Kalshi penalized three candidates—Matt Klein of Minnesota, Ezekiel Enriquez of Texas, and Virginia independent Mark Moran—for betting on their own campaigns. Moran stated he wagered on himself to highlight the system’s vulnerabilities. Kalshi has also reportedly blocked dozens of attempts by campaign staffers to trade based on insider information since May.
Additional instances of insider trading have drawn legal scrutiny, such as a case involving an Army special forces soldier charged with using classified details about an operation in Venezuela to profit on Polymarket. These examples illustrate challenges in enforcing regulations designed primarily for traditional financial markets, as existing laws do not fully address the unique characteristics of prediction platforms.
Regulatory responses vary, with the U.S. Commodity Futures Trading Commission overseeing platforms like Kalshi and Polymarket’s U.S. operations, while state authorities have issued cease-and-desist orders or pursued litigation. New Jersey’s attorney general has petitioned the U.S. Supreme Court to allow state gambling laws to apply to these markets after an appeals court ruled in Kalshi’s favor. Meanwhile, the Senate unanimously banned senators and staff from betting on prediction markets, though the House has yet to enact a comparable restriction.
As the 2026 midterms unfold under these evolving circumstances, experts warn that the rapid growth of prediction market trading may exacerbate risks related to misinformation, insider trading, and election integrity. The platforms contend that market manipulation attempts are counteracted by competing traders and that users should interpret odds as probabilistic estimates rather than definitive predictions. Nonetheless, calls persist for stricter enforcement, clearer regulation, and heightened penalties to deter misconduct and ensure the markets do not undermine public confidence in the democratic process.